I am a third-year CS PhD student in Language Technologies Institute at Carnegie Mellon University (CMU), and fortunate to be advised by Prof. Eric Xing. Previously, I completed my MS in computer science at CMU under the guidance of Prof. Jaime Carbonell. Prior to CMU, I earned BS in Electrical Engineering and Mathematics from Seoul National University.
My research focuses on large-scale meta-learning (or multilevel optimization) and its applications to AutoML.
Betty: An Automatic Differentiation Library for Multilevel Optimization. Preprint, 2022.
Sang Keun Choe, Willie Neiswanger, Pengtao Xie, and Eric Xing
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning. OSDI, 2021.
Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Greg Ganger, and Eric P. Xing
🏆 Jay Lepreau Best Paper Award!
On Orthogonal Jacobian Regularization in Deep Neural Networks. SEDL Workshop @ NeurIPS, 2019.
Sang Keun Choe*, Hosan Jeong*, and Jaime Carbonell
On Leveraging the Visual Modality for Neural Machine Translation. INLG, 2019.
Vikas Raunak*, Sang Keun Choe*, Quanyang Lu*, Yi Xu*, and Florian Metze
Audio Cover Song Identification using Convolutional Neural Network. ICASSP, 2018.
Sungkyung Chang, Juheon Lee, Sang Keun Choe, and Kyogu Lee
Sansom Presidential Scholarship,
Carnegie Mellon University.
Jay Lepreau Best Paper Award, OSDI. 2021
Kwanjeong Scholarship for Graduate Study, Kwanjeong Educational Foundation. 2018
Best Undergraduate Engineering Student Award, Seoul National University. 2018
Summa Cum Laude, Seoul National University. 2018
Presidential Scholarship for Science and Engineering Study, Korea Student Aid Foundation. 2011
Gold Medal, Korea Collegiate Mathematical Competition. 2011
Silver Medal, Korea Mathematical Olympiad. 2010